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Quick Reference of Matplotlib

Last modified: Oct, 2015

General info

A typical plotting script using Matplotlib

This script tries to do the similar task with the example script in Matlab.

import numpy as np
import matplotlib.pyplot as plt

#plt.close()
plt.figure(1, figsize=(10,8))   # figure size 10" by 8"
ax = plt.subplot(111)
x = np.linspace(0,2*np.pi, 100) 
y1 = np.sin(x)
y2 = np.cos(x)
lines = plt.plot(x, y1, 'b-', x, y2, 'r--')
plt.setp(lines, 'linewidth', 3)
plt.xlabel('x')
plt.ylabel('y')
plt.xlim([0, 2*np.pi])
plt.ylim([-2, 2])
ax.xaxis.label.set_fontsize(18)   # set x-axis label font size 
ax.yaxis.label.set_fontsize(18)   # set y-axis label font size 
for item in (ax.get_xticklabels() + ax.get_yticklabels()):
    item.set_fontsize(18)   # set axis tick font size
plt.legend(['sin(x)', 'cos(x)'], loc = 'lower left', prop={'size':'20'})   # loc: legend location
plt.show()

Plot multiple y axes/scales in a single plot

See the official example here, using ax.twinx(). My example:

plt.figure(1, figsize=(10, 8))
ax = plt.subplot(111)
plt.plot(t1, f1)
plt.xlabel('t')
plt.ylabel('f')
plt.ylim([0, 1000])
plt.legend(["f1"], loc="upper left")
ax.xaxis.label.set_fontsize(18)   # set x-axis label font size
ax.yaxis.label.set_fontsize(18)   # set y-axis label font size
for item in (ax.get_xticklabels() + ax.get_yticklabels()):
    item.set_fontsize(18)   # set axis tick font size

ax2 = ax.twinx()
plt.plot(t1, T1, '--r')
plt.legend(["T"], loc="upper right")
plt.ylabel('T')
plt.ylim([-5, 60])
ax2.xaxis.label.set_fontsize(18)   # set x-axis label font size
ax2.yaxis.label.set_fontsize(18)   # set y-axis label font size
for item in (ax2.get_xticklabels() + ax2.get_yticklabels()):
    item.set_fontsize(18)   # set axis tick font size

Import data

Alternative to the “importdata” function in Matlab, Numpy has “loadtxt”. For exapmle:

import numpy as np
data = np.loadtxt('data.dat', skiprows=1)  # skip the first row during the import

Add text to plots

Usually there are two ways:

Use matplotlib.pyplot.text(xpos, ypos, string). For example:

import numpy as np
import matplotlib.pyplot as plt

plt.text(1, 2, 'this is text')

Extra manipulation such as text wrapping can be found here.

Use matplotlib.pyplot.annotate. Refer to this link.

Use TeX for rendering text

Enable TeX rendering by

import matplotlib.pyplot as plt
plt.rc('text', usetex=True)

Working with directory

Sometimes one needs to import many data files to the workspace and plot. This can be realized with the help of package “glob” which is capable of matching wildcards in path patterns. For example,

import numpy as np 
import matplotlib.pyplot as plt
import glob

data_files = glob.glob('data*.dat') 
# data_files will be a string array containing all files matching 'data*.dat' pattern

plt.figure(1)
for d in data_files: 
    data = np.loadtxt(d)
    plt.loglog(data[:,0], data[:,1])  # assuming data is a 2D array
plt.show()